import pandas as pd, pickle, numpy as np, matplotlib.pyplot as plt, matplotlib.dates as mdates, matplotlib as mpl
import matplotlib.lines as mlines
from datetime import datetime, timedelta
#%run safegraph_census.ipynb
#%run create_master_table.ipynb
with open('covid_data.p', 'rb') as f:
data = pickle.load(f)
%run graphFunctions.ipynb
print("Total Deaths :", data[data.date == data.date.max()- timedelta(days=0)].deaths_cdc.sum())
Total Deaths : 423566.0
plotStateTotals(data, 'deaths_cdc', 'deaths_cdc', 200)
plotStateTotals(data, 'deaths_cdc', 'deaths_cdc_per_100k', 200)
states=data.state_code.unique()
stateGraphs(data, states,'confirmed_cdc','deaths_cdc', '2020-03-01', 21)
states = getStatesInRegion("N").keys()
stateGraphs(data, states,'confirmed_cdc','deaths_cdc', '2020-03-01', 21)
states = getStatesInRegion("S").keys()
stateGraphs(data, states,'confirmed_cdc','deaths_cdc', '2020-03-01', 21)
states = getStatesInRegion("M").keys()
stateGraphs(data, states,'confirmed_cdc','deaths_cdc', '2020-03-01', 21)
states = getStatesInRegion("W").keys()
stateGraphs(data, states,'confirmed_cdc','deaths_cdc', '2020-03-01', 21)
states = getStatesInRegion("O").keys()
stateGraphs(data, states,'confirmed_cdc','deaths_cdc', '2020-03-01', 21)
#
#
#
state = 'NY'
death_min = 500
stateGraphs(data, [state],'confirmed_cdc','deaths_cdc', '2020-03-01', 7)
plotCountyDeathCurves(data, state, death_min = death_min, rolling_ave = 14, start_date='2020-03-14')
graphMobilityCounty(data, state, '2020-03-01', 1, death_min = death_min)
graphMobilityCounty(data, state, '2020-03-01', 14, death_min = death_min)
plotInteractions(data, 'pop_density_percentile', 'age_55_plus_pct_percentile', 'deaths_per_100k',[state])
plotInteractions(data, 'pop_density_percentile', 'r_white_pct_percentile', 'deaths_per_100k',[state])
plotInteractions(data, 'pop_density_percentile', 'unins_pct_percentile', 'deaths_per_100k',[state])
plotInteractions(data, 'unins_pct_percentile', 'pir_200_plus_pct_percentile', 'deaths_per_100k',[state])
# # # #
state = 'CA'
death_min = 600
stateGraphs(data, [state],'confirmed_cdc','deaths_cdc', '2020-03-01', 7)
plotCountyDeathCurves(data, state, death_min = death_min, rolling_ave = 14, start_date='2020-03-14')
graphMobilityCounty(data, state, '2020-03-01', 1, death_min = death_min)
graphMobilityCounty(data, state, '2020-03-01', 14, death_min = death_min)
plotInteractions(data, 'pop_density_percentile', 'age_55_plus_pct_percentile', 'deaths_per_100k',[state])
plotInteractions(data, 'pop_density_percentile', 'r_white_pct_percentile', 'deaths_per_100k',[state])
plotInteractions(data, 'pop_density_percentile', 'unins_pct_percentile', 'deaths_per_100k',[state])
plotInteractions(data, 'unins_pct_percentile', 'pir_200_plus_pct_percentile', 'deaths_per_100k',[state])
# # # #
state = 'TX'
death_min = 500
stateGraphs(data, [state],'confirmed_cdc','deaths_cdc', '2020-03-01', 7)
plotCountyDeathCurves(data, state, death_min = death_min, rolling_ave = 14, start_date='2020-03-14')
graphMobilityCounty(data, state, '2020-03-01', 1, death_min = death_min)
graphMobilityCounty(data, state, '2020-03-01', 14, death_min = death_min)
plotInteractions(data, 'pop_density_percentile', 'age_55_plus_pct_percentile', 'deaths_per_100k',[state])
plotInteractions(data, 'pop_density_percentile', 'r_white_pct_percentile', 'deaths_per_100k',[state])
plotInteractions(data, 'pop_density_percentile', 'unins_pct_percentile', 'deaths_per_100k',[state])
plotInteractions(data, 'unins_pct_percentile', 'pir_200_plus_pct_percentile', 'deaths_per_100k',[state])
# # # #
state = 'FL'
death_min = 500
stateGraphs(data, [state],'confirmed_cdc','deaths_cdc', '2020-03-01', 7)
plotCountyDeathCurves(data, state, death_min = death_min, rolling_ave = 14, start_date='2020-03-14')
graphMobilityCounty(data, state, '2020-03-01', 1, death_min = death_min)
graphMobilityCounty(data, state, '2020-03-01', 14, death_min = death_min)
plotInteractions(data, 'pop_density_percentile', 'age_55_plus_pct_percentile', 'deaths_per_100k',[state])
plotInteractions(data, 'pop_density_percentile', 'r_white_pct_percentile', 'deaths_per_100k',[state])
plotInteractions(data, 'pop_density_percentile', 'unins_pct_percentile', 'deaths_per_100k',[state])
plotInteractions(data, 'unins_pct_percentile', 'pir_200_plus_pct_percentile', 'deaths_per_100k',[state])
# # # #
state = 'NJ'
death_min = 500
stateGraphs(data, [state],'confirmed_cdc','deaths_cdc', '2020-03-01', 7)
plotCountyDeathCurves(data, state, death_min = death_min, rolling_ave = 14, start_date='2020-03-14')
graphMobilityCounty(data, state, '2020-03-01', 1, death_min = death_min)
graphMobilityCounty(data, state, '2020-03-01', 14, death_min = death_min)
plotInteractions(data, 'pop_density_percentile', 'age_55_plus_pct_percentile', 'deaths_per_100k',[state])
plotInteractions(data, 'pop_density_percentile', 'r_white_pct_percentile', 'deaths_per_100k',[state])
plotInteractions(data, 'pop_density_percentile', 'unins_pct_percentile', 'deaths_per_100k',[state])
plotInteractions(data, 'unins_pct_percentile', 'pir_200_plus_pct_percentile', 'deaths_per_100k',[state])
# # # #
state = 'PA'
death_min = 500
stateGraphs(data, [state],'confirmed_cdc','deaths_cdc', '2020-03-01', 7)
plotCountyDeathCurves(data, state, death_min = death_min, rolling_ave = 14, start_date='2020-03-14')
graphMobilityCounty(data, state, '2020-03-01', 1, death_min = death_min)
graphMobilityCounty(data, state, '2020-03-01', 14, death_min = death_min)
plotInteractions(data, 'pop_density_percentile', 'age_55_plus_pct_percentile', 'deaths_per_100k',[state])
plotInteractions(data, 'pop_density_percentile', 'r_white_pct_percentile', 'deaths_per_100k',[state])
plotInteractions(data, 'pop_density_percentile', 'unins_pct_percentile', 'deaths_per_100k',[state])
plotInteractions(data, 'unins_pct_percentile', 'pir_200_plus_pct_percentile', 'deaths_per_100k',[state])
# # # #
state = 'IL'
death_min = 300
stateGraphs(data, [state],'confirmed_cdc','deaths_cdc', '2020-03-01', 7)
plotCountyDeathCurves(data, state, death_min = death_min, rolling_ave = 14, start_date='2020-03-14')
graphMobilityCounty(data, state, '2020-03-01', 1, death_min = death_min)
graphMobilityCounty(data, state, '2020-03-01', 14, death_min = death_min)
plotInteractions(data, 'pop_density_percentile', 'age_55_plus_pct_percentile', 'deaths_per_100k',[state])
plotInteractions(data, 'pop_density_percentile', 'r_white_pct_percentile', 'deaths_per_100k',[state])
plotInteractions(data, 'pop_density_percentile', 'unins_pct_percentile', 'deaths_per_100k',[state])
plotInteractions(data, 'unins_pct_percentile', 'pir_200_plus_pct_percentile', 'deaths_per_100k',[state])
# # # #
state = 'MA'
death_min = 300
stateGraphs(data, [state],'confirmed_cdc','deaths_cdc', '2020-03-01', 7)
plotCountyDeathCurves(data, state, death_min = death_min, rolling_ave = 14, start_date='2020-03-14')
graphMobilityCounty(data, state, '2020-03-01', 1, death_min = death_min)
graphMobilityCounty(data, state, '2020-03-01', 14, death_min = death_min)
plotInteractions(data, 'pop_density_percentile', 'age_55_plus_pct_percentile', 'deaths_per_100k',[state])
plotInteractions(data, 'pop_density_percentile', 'r_white_pct_percentile', 'deaths_per_100k',[state])
plotInteractions(data, 'pop_density_percentile', 'unins_pct_percentile', 'deaths_per_100k',[state])
plotInteractions(data, 'unins_pct_percentile', 'pir_200_plus_pct_percentile', 'deaths_per_100k',[state])
# # # #
state = 'AZ'
death_min = 300
stateGraphs(data, [state],'confirmed_cdc','deaths_cdc', '2020-03-01', 7)
plotCountyDeathCurves(data, state, death_min = death_min, rolling_ave = 14, start_date='2020-03-14')
graphMobilityCounty(data, state, '2020-03-01', 1, death_min = death_min)
graphMobilityCounty(data, state, '2020-03-01', 14, death_min = death_min)
plotInteractions(data, 'pop_density_percentile', 'age_55_plus_pct_percentile', 'deaths_per_100k',[state])
plotInteractions(data, 'pop_density_percentile', 'r_white_pct_percentile', 'deaths_per_100k',[state])
plotInteractions(data, 'pop_density_percentile', 'unins_pct_percentile', 'deaths_per_100k',[state])
plotInteractions(data, 'unins_pct_percentile', 'pir_200_plus_pct_percentile', 'deaths_per_100k',[state])
# # # #
state = 'MI'
death_min = 300
stateGraphs(data, [state],'confirmed_cdc','deaths_cdc', '2020-03-01', 7)
plotCountyDeathCurves(data, state, death_min = death_min, rolling_ave = 14, start_date='2020-03-14')
graphMobilityCounty(data, state, '2020-03-01', 1, death_min = death_min)
graphMobilityCounty(data, state, '2020-03-01', 14, death_min = death_min)
plotInteractions(data, 'pop_density_percentile', 'age_55_plus_pct_percentile', 'deaths_per_100k',[state])
plotInteractions(data, 'pop_density_percentile', 'r_white_pct_percentile', 'deaths_per_100k',[state])
plotInteractions(data, 'pop_density_percentile', 'unins_pct_percentile', 'deaths_per_100k',[state])
plotInteractions(data, 'unins_pct_percentile', 'pir_200_plus_pct_percentile', 'deaths_per_100k',[state])
# # # #
states = getStatesInRegion("N").keys()
statesCompare(data, states, 'confirmed_cdc', 'deaths_cdc', '2020-03-01', 14)
states = getStatesInRegion("S").keys()
statesCompare(data, states, 'confirmed_cdc', 'deaths_cdc', '2020-03-01', 14)
states = getStatesInRegion("M").keys()
statesCompare(data, states, 'confirmed_cdc', 'deaths_cdc', '2020-03-01', 14)
states = getStatesInRegion("W").keys()
statesCompare(data, states, 'confirmed_cdc', 'deaths_cdc', '2020-03-01', 14)
states = getStatesInRegion("O").keys()
statesCompare(data, states, 'confirmed_cdc', 'deaths_cdc', '2020-03-01', 14)
# # # #
states = list(data.state_code.unique())
plotGroupedDeathCurves(data, states=states, rolling_ave=30, bycol='pop_density_grp', start_date='2020-03-01')
The race definition used here is 'white' as reported in census data. Low would be 'non-white' and high would be 'white'.
plotGroupedDeathCurves(data, states=states, rolling_ave=30, bycol='r_w_grp', start_date='2020-03-01')
'Low' are the counties with the lowest percentages of uninsured individuals.
plotGroupedDeathCurves(data, states=states, rolling_ave=30, bycol='unins_grp', start_date='2020-03-01')
'High' are the counties with the highest percentage of PIR > 200%
plotGroupedDeathCurves(data, states=states, rolling_ave=30, bycol='pir_grp', start_date='2020-03-01')
plotGroupedDeathCurves(data, states=states, rolling_ave=30, bycol='age_55_plus_grp', start_date='2020-03-01')